Report

Introduction to Geographic Information Systems at TU Dresden

Author

Tuan Linh Tran, Andrea Češková, Tobias Grüner

Goal of the analysis

Research question: How does the relationship between population density and temperature vary across different land use types around Netherlands?

Data

Scope

Figure 1: Districts in the Netherlands

Outcome variable: Temperature

Figure 2: Average Temperature Across the Netherlands

Control variable: Population density

Summary Statistics

Table 1: Summary statistics
Land Use Type Sample Size Mean Temperature (°C) SD Temperature (°C) Mean Population Median Population Correlation temperature ~ population
Forests 1,644 11.16 0.29 2.57 1.49 0.08
Urban fabric 1,555 11.21 0.27 7.68 5.91 0.11
Industrial, commercial and transport units 1,109 11.22 0.24 6.50 4.65 0.02
Artificial, non-agricultural vegetated areas 1,036 11.19 0.26 7.71 4.92 0.03
Heterogeneous agricultural areas 888 11.23 0.27 2.82 1.87 0.14
Arable land 802 11.23 0.26 2.88 1.81 0.10
Pastures 736 11.22 0.27 3.57 2.19 0.05
Scrub and/or herbaceous vegetation associations 603 11.15 0.31 2.16 1.15 0.11
Inland waters 420 11.17 0.28 3.72 2.09 0.18
Inland wetlands 278 11.15 0.28 2.46 1.19 0.05
Mine, dump and construction sites 258 11.22 0.25 5.07 2.74 0.00
Permanent crops 75 11.31 0.14 2.21 1.63 -0.13
Maritime wetlands 74 11.37 0.26 1.12 0.57 0.30
Open spaces with little or no vegetation 58 11.26 0.24 2.13 0.81 0.20
Marine waters 5 11.17 0.35 2.47 2.62 -0.69
Source: Data from Netherlands 2019: Temperature (CHELSA), Population (WorldPop), Land Use (Corine)
Figure 3: Correlation between Temperature and Population by Land Use Type across the Netherlands

Regression models

Table 2: Regression Results
Outcome Variable: Temperature in °C
Variable Model 1: Population Only1 Model 2: Land Use Only2 Model 3: Full Model3
Intercept 11.158*** (0.007) 11.206*** (0.004) 11.154*** (0.012)
Log(Population + 1) 0.031*** (0.004) 0.027*** (0.006)
Log(Pop) × Land Use: Agricultural areas 0.026* (0.012)
Log(Pop) × Land Use: Forest and semi natural areas 0.041** (0.014)
Log(Pop) × Land Use: Water bodies 0.076** (0.029)
Log(Pop) × Land Use: Wetlands -0.007 (0.034)
landuseAgricultural areas 0.022** (0.007) 0.009 (0.019)
landuseForest and semi natural areas -0.045*** (0.007) -0.046* (0.020)
landuseWater bodies -0.035* (0.014) -0.125** (0.043)
landuseWetlands -0.007 (0.015) 0.021 (0.040)
Standard errors in parentheses. Significance: † p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
1 n = 7,486 | R² = 0.007 | Adj. R² = 0.007 | RMSE = 0.262
2 n = 9,528 | R² = 0.008 | Adj. R² = 0.008 | RMSE = 0.271
3 n = 7,486 | R² = 0.016 | Adj. R² = 0.014 | RMSE = 0.261

The analysis of temperature patterns across the Netherlands reveal that areas with higher population density consistently experience elevated temperatures. Model 1 demonstrates that a logarithmic increase in population density corresponds to a 0.031°C increase in temperature.

If we take a look at the Model 2, where we differenciate between different land use types, we can see that agricultural areas show slightly elevated temperatures, while forested and semi-natural areas provide significant cooling effects, reducing temperatures by approximately 0.045°C. Water bodies also contribute to local cooling, though to a lesser extent than forests. Wetlands show no significant temperature deviation from the baseline, suggesting they maintain relatively neutral thermal characteristics.

The most interesting findings emerge from the interaction between population density and land use type in the full model. Water bodies demonstrate the strongest interaction effect, where populated areas near water experience amplified warming despite water’s typical cooling properties. Similarly, forested areas with higher population density show increased temperatures, suggesting that human development can override the natural cooling benefits of vegetation. Agricultural areas exhibit a weaker but still significant interaction, while wetlands appear to buffer against population-related temperature increases, showing no significant interaction effect.

These results indicate that land use type serves as an important moderator in the population-temperature relationship. While the overall explanatory power remains modest, with R2 values between 0.007 and 0.016, the findings demonstrate that the urban heat island effect varies significantly depending on the surrounding land use context. This suggests that urban planning strategies should consider not just population density but also the thermal characteristics of different land use types when addressing local climate impacts.